Abstract
The influence maximization problem aims to identify influential nodes allowing to reach the viral marketing objectives on social networks. Previous researches are mainly concerned with the static social network analysis and the development of algorithms in this context. However, when network changes, those algorithms must be updated. In this paper, we offer a new interesting approach to study the influential nodes detection problem in changing social networks. This approach can be considered to be an extension of a previous static algorithm SND (Semantic and structural influential Nodes Detection). Experimental results prove the effectiveness of SNDUpdate to detect influential nodes in dynamic social networks.
MARS—Modeling of Automated Reasoning Systems.
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Hafiene, N., Karoui, W., Ben Romdhane, L. (2019). Influential Nodes Detection in Dynamic Social Networks. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems. BIS 2019. Lecture Notes in Business Information Processing, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-030-20482-2_6
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DOI: https://doi.org/10.1007/978-3-030-20482-2_6
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